#
# Copyright 2015 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from unittest import TestCase

from nose_parameterized import parameterized
from numpy import (
    arange,
    datetime64,
)
from numpy.testing import (
    assert_array_equal,
)
from pandas import (
    DataFrame,
    DatetimeIndex,
    Timestamp,
)
from pandas.util.testing import assert_index_equal
from testfixtures import TempDirectory

from zipline.pipeline.loaders.synthetic import (
    SyntheticDailyBarWriter,
)
from zipline.data.us_equity_pricing import (
    BcolzDailyBarReader,
    NoDataOnDate
)
from zipline.finance.trading import TradingEnvironment
from zipline.pipeline.data import USEquityPricing
from zipline.testing import seconds_to_timestamp

TEST_CALENDAR_START = Timestamp('2015-06-01', tz='UTC')
TEST_CALENDAR_STOP = Timestamp('2015-06-30', tz='UTC')

TEST_QUERY_START = Timestamp('2015-06-10', tz='UTC')
TEST_QUERY_STOP = Timestamp('2015-06-19', tz='UTC')

# One asset for each of the cases enumerated in load_raw_arrays_from_bcolz.
EQUITY_INFO = DataFrame(
    [
        # 1) The equity's trades start and end before query.
        {'start_date': '2015-06-01', 'end_date': '2015-06-05'},
        # 2) The equity's trades start and end after query.
        {'start_date': '2015-06-22', 'end_date': '2015-06-30'},
        # 3) The equity's data covers all dates in range.
        {'start_date': '2015-06-02', 'end_date': '2015-06-30'},
        # 4) The equity's trades start before the query start, but stop
        #    before the query end.
        {'start_date': '2015-06-01', 'end_date': '2015-06-15'},
        # 5) The equity's trades start and end during the query.
        {'start_date': '2015-06-12', 'end_date': '2015-06-18'},
        # 6) The equity's trades start during the query, but extend through
        #    the whole query.
        {'start_date': '2015-06-15', 'end_date': '2015-06-25'},
    ],
    index=arange(1, 7),
    columns=['start_date', 'end_date'],
).astype(datetime64)

TEST_QUERY_ASSETS = EQUITY_INFO.index


class BcolzDailyBarTestCase(TestCase):

    @classmethod
    def setUpClass(cls):
        all_trading_days = TradingEnvironment().trading_days
        cls.trading_days = all_trading_days[
            all_trading_days.get_loc(TEST_CALENDAR_START):
            all_trading_days.get_loc(TEST_CALENDAR_STOP) + 1
        ]

    def setUp(self):

        self.asset_info = EQUITY_INFO
        self.writer = SyntheticDailyBarWriter(
            self.asset_info,
            self.trading_days,
        )

        self.dir_ = TempDirectory()
        self.dir_.create()
        self.dest = self.dir_.getpath('daily_equity_pricing.bcolz')

    def tearDown(self):
        self.dir_.cleanup()

    @property
    def assets(self):
        return self.asset_info.index

    def trading_days_between(self, start, end):
        return self.trading_days[self.trading_days.slice_indexer(start, end)]

    def asset_start(self, asset_id):
        return self.writer.asset_start(asset_id)

    def asset_end(self, asset_id):
        return self.writer.asset_end(asset_id)

    def dates_for_asset(self, asset_id):
        start, end = self.asset_start(asset_id), self.asset_end(asset_id)
        return self.trading_days_between(start, end)

    def test_write_ohlcv_content(self):
        result = self.writer.write(self.dest, self.trading_days, self.assets)
        for column in SyntheticDailyBarWriter.OHLCV:
            idx = 0
            data = result[column][:]
            multiplier = 1 if column == 'volume' else 1000
            for asset_id in self.assets:
                for date in self.dates_for_asset(asset_id):
                    self.assertEqual(
                        SyntheticDailyBarWriter.expected_value(
                            asset_id,
                            date,
                            column
                        ) * multiplier,
                        data[idx],
                    )
                    idx += 1
            self.assertEqual(idx, len(data))

    def test_write_day_and_id(self):
        result = self.writer.write(self.dest, self.trading_days, self.assets)
        idx = 0
        ids = result['id']
        days = result['day']
        for asset_id in self.assets:
            for date in self.dates_for_asset(asset_id):
                self.assertEqual(ids[idx], asset_id)
                self.assertEqual(date, seconds_to_timestamp(days[idx]))
                idx += 1

    def test_write_attrs(self):
        result = self.writer.write(self.dest, self.trading_days, self.assets)
        expected_first_row = {
            '1': 0,
            '2': 5,   # Asset 1 has 5 trading days.
            '3': 12,  # Asset 2 has 7 trading days.
            '4': 33,  # Asset 3 has 21 trading days.
            '5': 44,  # Asset 4 has 11 trading days.
            '6': 49,  # Asset 5 has 5 trading days.
        }
        expected_last_row = {
            '1': 4,
            '2': 11,
            '3': 32,
            '4': 43,
            '5': 48,
            '6': 57,    # Asset 6 has 9 trading days.
        }
        expected_calendar_offset = {
            '1': 0,   # Starts on 6-01, 1st trading day of month.
            '2': 15,  # Starts on 6-22, 16th trading day of month.
            '3': 1,   # Starts on 6-02, 2nd trading day of month.
            '4': 0,   # Starts on 6-01, 1st trading day of month.
            '5': 9,   # Starts on 6-12, 10th trading day of month.
            '6': 10,  # Starts on 6-15, 11th trading day of month.
        }
        self.assertEqual(result.attrs['first_row'], expected_first_row)
        self.assertEqual(result.attrs['last_row'], expected_last_row)
        self.assertEqual(
            result.attrs['calendar_offset'],
            expected_calendar_offset,
        )
        assert_index_equal(
            self.trading_days,
            DatetimeIndex(result.attrs['calendar'], tz='UTC'),
        )

    def _check_read_results(self, columns, assets, start_date, end_date):
        table = self.writer.write(self.dest, self.trading_days, self.assets)
        reader = BcolzDailyBarReader(table)
        results = reader.load_raw_arrays(columns, start_date, end_date, assets)
        dates = self.trading_days_between(start_date, end_date)
        for column, result in zip(columns, results):
            assert_array_equal(
                result,
                self.writer.expected_values_2d(
                    dates,
                    assets,
                    column.name,
                )
            )

    @parameterized.expand([
        ([USEquityPricing.open],),
        ([USEquityPricing.close, USEquityPricing.volume],),
        ([USEquityPricing.volume, USEquityPricing.high, USEquityPricing.low],),
        (USEquityPricing.columns,),
    ])
    def test_read(self, columns):
        self._check_read_results(
            columns,
            self.assets,
            TEST_QUERY_START,
            TEST_QUERY_STOP,
        )

    def test_start_on_asset_start(self):
        """
        Test loading with queries that starts on the first day of each asset's
        lifetime.
        """
        columns = [USEquityPricing.high, USEquityPricing.volume]
        for asset in self.assets:
            self._check_read_results(
                columns,
                self.assets,
                start_date=self.asset_start(asset),
                end_date=self.trading_days[-1],
            )

    def test_start_on_asset_end(self):
        """
        Test loading with queries that start on the last day of each asset's
        lifetime.
        """
        columns = [USEquityPricing.close, USEquityPricing.volume]
        for asset in self.assets:
            self._check_read_results(
                columns,
                self.assets,
                start_date=self.asset_end(asset),
                end_date=self.trading_days[-1],
            )

    def test_end_on_asset_start(self):
        """
        Test loading with queries that end on the first day of each asset's
        lifetime.
        """
        columns = [USEquityPricing.close, USEquityPricing.volume]
        for asset in self.assets:
            self._check_read_results(
                columns,
                self.assets,
                start_date=self.trading_days[0],
                end_date=self.asset_start(asset),
            )

    def test_end_on_asset_end(self):
        """
        Test loading with queries that end on the last day of each asset's
        lifetime.
        """
        columns = [USEquityPricing.close, USEquityPricing.volume]
        for asset in self.assets:
            self._check_read_results(
                columns,
                self.assets,
                start_date=self.trading_days[0],
                end_date=self.asset_end(asset),
            )

    def test_unadjusted_spot_price(self):
        table = self.writer.write(self.dest, self.trading_days, self.assets)
        reader = BcolzDailyBarReader(table)
        # At beginning
        price = reader.spot_price(1, Timestamp('2015-06-01', tz='UTC'),
                                  'close')
        # Synthetic writes price for date.
        self.assertEqual(135630.0, price)

        # Middle
        price = reader.spot_price(1, Timestamp('2015-06-02', tz='UTC'),
                                  'close')
        self.assertEqual(135631.0, price)
        # End
        price = reader.spot_price(1, Timestamp('2015-06-05', tz='UTC'),
                                  'close')
        self.assertEqual(135634.0, price)

        # Another sid at beginning.
        price = reader.spot_price(2, Timestamp('2015-06-22', tz='UTC'),
                                  'close')
        self.assertEqual(235651.0, price)

        # Ensure that volume does not have float adjustment applied.
        volume = reader.spot_price(1, Timestamp('2015-06-02', tz='UTC'),
                                   'volume')
        self.assertEqual(145631, volume)

    def test_unadjusted_spot_price_no_data(self):
        table = self.writer.write(self.dest, self.trading_days, self.assets)
        reader = BcolzDailyBarReader(table)
        # before
        with self.assertRaises(NoDataOnDate):
            reader.spot_price(2, Timestamp('2015-06-08', tz='UTC'), 'close')

        # after
        with self.assertRaises(NoDataOnDate):
            reader.spot_price(4, Timestamp('2015-06-16', tz='UTC'), 'close')

    def test_unadjusted_spot_price_empty_value(self):
        table = self.writer.write(self.dest, self.trading_days, self.assets)
        reader = BcolzDailyBarReader(table)

        # A sid, day and corresponding index into which to overwrite a zero.
        zero_sid = 1
        zero_day = Timestamp('2015-06-02', tz='UTC')
        zero_ix = reader.sid_day_index(zero_sid, zero_day)

        # Write a zero into the synthetic pricing data at the day and sid,
        # so that a read should now return -1.
        # This a little hacky, in lieu of changing the synthetic data set.
        reader._spot_col('close')[zero_ix] = 0

        close = reader.spot_price(zero_sid, zero_day, 'close')
        self.assertEqual(-1, close)
